Results 1 to 10 of about 114,441 (314)
On the Orthogonal Basis of Symmetry Classes of Tensors
Journal of Algebra, 2001 Let \(V\) be an \(n\)-dimensional inner product vector space over the complex field \(\mathbb{C}\). Let \(G\) be a subgroup of the symmetric group \(S_m\) on \(m\) letters and \(\chi\) be an irreducible complex character of \(G\). For \(g\in G\), the mapping \(P_g\colon\bigotimes^m_1V\to\bigotimes^m_1V\) is defined by \(P_g(v_1\otimes\cdots\otimes v_m)=
Shahabi, M.A, Azizi, K, Jafari, M.H
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Orthogonal Basis-Based Multiview Transfer Spectral Clustering [PDF]
Jisuanji gongcheng, 2022 The consistency of multiview data is important for multiview clustering.To achieve multiview data with better consistency, this paper proposes a new multiview clustering algorithm, OMTSC.The OMTSC algorithm simultaneously learns the cluster assignment ...
WANG Lijuan, ZHANG Lin, YIN Ming, HAO Zhifeng, CAI Ruichu, WEN Wen
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Современная наука и инновации, 2023 The paper developed a method for obtaining sequences of discrete signals, which greatly simplifies the process of obtaining signal sequences with new autocorrelation and spectral characteristics, based on the properties of orthogonal transformations of ...
V. M. Samus
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Spectra of Self-Similar Measures
Entropy, 2022 This paper is devoted to the characterization of spectrum candidates with a new tree structure to be the spectra of a spectral self-similar measure μN,D generated by the finite integer digit set D and the compression ratio N−1.
Yong-Shen Cao +2 more
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A reduced basis localized orthogonal decomposition [PDF]
Journal of Computational Physics, 2015 In this work we combine the framework of the Reduced Basis method (RB) with the framework of the Localized Orthogonal Decomposition (LOD) in order to solve parametrized elliptic multiscale problems. The idea of the LOD is to split a high dimensional Finite Element space into a low dimensional space with comparably good approximation properties and a ...
Abdulle, Assyr, Henning, Patrick
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Orthogonal basis for the optical transfer function [PDF]
Applied Optics, 2016 We propose systems of orthogonal functions qn to represent optical transfer functions (OTF) characterized by including the diffraction-limited OTF as the first basis function q0=OTFperfect. To this end, we apply a powerful and rigorous theoretical framework based on applying the appropriate change of variables to well-known orthogonal systems.
Ferreira, C. +3 more
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Detecting multipartite entanglement via complete orthogonal basis
Results in Physics, 2023 We study genuine tripartite entanglement and multipartite entanglement in arbitrary n-partite quantum systems based on complete orthogonal basis (COB). While the usual Bloch representation of a density matrix uses three types of generators, the density ...
Hui Zhao +5 more
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Computing an LLL-reduced Basis of the Orthogonal Latice [PDF]
Proceedings of the 2018 ACM International Symposium on Symbolic and Algebraic Computation, 2018 As a typical application, the Lenstra-Lenstra-Lovasz lattice basis reduction algorithm (LLL) is used to compute a reduced basis of the orthogonal lattice for a given integer matrix, via reducing a special kind of lattice bases. With such bases in input, we propose a new technique for bounding from above the number of iterations required by the LLL ...
Chen, Jingwei +2 more
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Using Generalized Basis for Functional Expansion
Journal of Nuclear Engineering, 2021 Functional expansion has been rigorously studied as a promising method in stochastic neutron transport and multi-physics coupling. It is a method to represent data specified on a desired domain as an expansion of basis set in a continuous manner.
Zhuoran Han, Benoit Forget, Kord Smith
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Stability on the basis of Orthogonal Trajectories [PDF]
Canadian Mathematical Bulletin, 1965 We consider a system of differential equations of second order given by1(' = d/dt) where P and Q have continuous first partial derivatives with respect to x and y in some open and simply connected set R containing O = (0, 0) which we assume to be the only singular point in R.
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